Toqito

- Feature: Added `in_separable_ball.py` under `state_props/`. Knowing whether a
density matrix (quantum state) is contained in the separable ball centered at
the maximally-mixed state is useful for separability testing. Added
`test_in_separable_ball.py` for unit testing.

- Feature: Added in ability to perform both minimum-error and unambiguous state
discrimination in `ppt_distinguishability.py`. Adding additional tests to
`ppt_state_distinguishability.py` to cover this extra feature.

- Feature: Added in ability to compute both primal and dual optimization
problems in `ppt_distinguishability.py`. This gives the user the capability
to obtain the measurement operators and also to use the computationally
efficiency of the dual problem to make quicker numeric calculations.

- Feature: Added `unvec.py` under `matrix_ops/`. This feature is the inverse of
pre-existing "vec" operation found in `vec.py`. That is, it allows one to take
a vector and transform it to a (possibly square) matrix.

- Feature: Added `choi_to_kraus.py` under `channel_ops/`. This feature allows
the user to convert a Choi matrix to a list of Kraus operators. This is the
inverse of the existing `kraus_to_choi.py` functionality that `toqito`
currently offers.

- Feature: Add `is_mutually_orthogonal.py` under `state_props/`. This feature
allows the user to determine whether a given set of states (vectors) are
mutually orthogonal with each other.

- Feature: Add `has_symmetric_extension.py` under `state_props/`. This feature
is very useful for determining whether a given state is entangled by checking
whether there exists a symmetric extension for that state.

- Feature: Add `cvx_kron.py` under `helper/`. This feature allows one to compute
the Kronecker product between two entities, where either two may be of type
`np.ndarray` or a `cvxpy` expression.

- Feature: Add `is_identity.py` to `state_props/`. This feature allows one to check
if a given matrix is equal to the identity matrix.

- Enhancement: Previously ignore tests for `channel_props/` are now being run as
part of the testing suite.

- Enhancement: More robust error checking and adding tolerance arguments for
various matrix properties found in `matrix_props/`.

- Doc-Fix: Trailing back-tick quotes removed in `li_norm_coherence.py`.

- Fix: Bug in `symmetric_extension_hierarchy.py` for `level=1` case. Added test
to cover this bug.

- Fix: Bug in `states/tile.py` produced 3-dimensional vectors when they should
have in fact been 9-dimensional vectors.

- Fix: Warning in testing suite for `test_symmetric_projection.py` for
previously using the deprecated `numpy.matrix` class has since been fixed and
the warning hence resolved.

- Fix: The `states/isotropic.py` file no longer requires the use of the
deprecated `numpy.matrix` class.

- Fix: Bug in `swap.py`. Added test to cover bug found.

- Fix: Bug in `ppt_distinguishability.py` that prevented checking for higher
dimensions. Added test to cover bug found.

- Fix: Bug in `ppt_distinguishability.py` that prevented checking 2-dimensional
cases.

- Fix: Bug in `state_distinguishability.py`. Value returned was being multiplied
by an unnecessary factor. Added other tests that would have caught this.

- Fix: Bug in `partial_trace.py`. Added test to cover bug found.

- Fix: Bug in `partial_transpose.py` for non-square matrices. Adding test cases to
cover this previously failing case.

- Fix: Bug in `purity.py`. Squaring matrix was using `**2` instead of
`np.linalg.matrix_power`

- Fix: Bug in `random_state_vector.py`. Added tests to cover.

- Fix: Bug in `schmidt_rank.py`. Added tests to cover.

- Feature: Added in `symmetric_extension_hierarchy.py`. The function is a
hierarchy of semidefinite programs that eventually converge to the separable
value for distinguishing an ensemble of quantum states. The first level is
just the standard PPT distinguishability probability. Computing higher levels
of this hierarchy can become intractable quite quickly.

- Feature: Added in ability to perform both minimum-error and unambiguous state
discrimination in `state_distinguishability.py`. Adding additional tests to
`test_state_distinguishability.py` to cover this extra feature.

- Feature: Added `majorizes.py`; a function to determine whether a vector or matrix
majorizes another. This is used as a criterion to determine whether a quantum
state can be converted to another via LOCC. Added `test_majorizes.py` for unit
testing.

- Feature: Added `perfect_matchings.py`; a function that calculates all the
perfect matchings of a given list of objects. Added
`test_perfect_matchings.py` for unit testing.

- Feature: Added `breuer.py` under `states/`; a specific bound-entangled state of
interest. Added in `test_breuer.py` for unit testing.

- Feature: Added `brauer.py` under `states/`. Added in `test_brauer.py` for unit
testing.

- Feature: Added `entanglement_of_formation.py` under `state_props/`. Added in
`test_entanglement_of_formation.py` for unit testing.

- Feature: Added `l1_norm_coherence.py` under `state_props/`. Added
`test_l1_norm_coherence.py` for unit testing.

- Enhancement: Adding further tests for `symmetric_projection.py`.

- Enhancement: Adding further tests for `ppt_distinguishability.py`.

- Enhancement: Adding further tests for `reduction.py`

- Enhancement: Consolidating `conclusive_state_exclusion.py` and
`unambiguous_state_exclusion.py` to just `state_exclusion.py`. Adding in
optional parameter to specify method of exclusion. Consolidated tests in
`test_state_exclusion.py`.